Value at Risk (VaR) approach has been extensively used by investment and commercial banks since its development by JP Morgan in 1990s. As time passes, it has become interesting to investigate whether VaR could be used also by other financial intermediaries like pension funds and insurance companies. The aim of this paper is to outline Value at Risk (VaR) methodology by giving more emphasis on parametric approach which is used for empirical section and to investigate the applicability and usefulness of VaR in pension funds. After providing theoretical framework for VaR approach, the paper continues with pension fund systems in general and especially highlights AP funds of Swedish National pension fund system by trying to show why VaR could be an invaluable risk management tool for these funds together with other traditional risk measures used. Based on this given theoretical frame, a practical application of VaR –parametric or covariance/variance method- is executed on 50 biggest investments in the fixed income and equity portfolios of three selected Swedish national pension funds – AP1, AP2 and AP3. Results of one day VaR (DEAR) estimations on 30/12/2005 for each fund have been presented and it is aimed to show the additional information that could be obtained by using VaR and which is not always apparent from other risk measures employed by funds. According to the two traditional risk measures which are active risk and Sharpe ratio; AP2 and AP3 lie in the same risk level for 2005 which can create a contradiction by considering their different returns. On the other hand, obtained DEAR estimates show their different risk exposures even with the 50 biggest investments employed. The results give a matching relationship between return of funds and DEAR estimates meaning that; the fund with the highest return has the highest DEAR value and the fund with the lowest return has the lowest DEAR value; which is consistent with the main rule- “higher risk, higher return”. Thus, we can conclude that VaR could be applied additionally to get a better picture about r...
